Tourist and Maine Resident Drive Time to the Proposed Katahdin Woods & Waters National Park
Bibliographic record
Abstract
We assess the drive times and the number of potential tourists and Maine residents that could visit the proposed Katahdin Woods & Waters National Park in Northern Maine. We used ArcGIS to calculate the drive times from potential North and South park entrances to eight locations: Acadia National Park, LL Bean (Freeport), Kennebunk, Bangor Airport, Portland Jetport, Boston Airport, Montreal Airport, and Quebec Airport. We also analyzed the number of households in Maine within a one, two, and three hour drive time of the proposed park. We conclude that there are 153,000 households within a three hour drive time of the park, which is 27.6% of all households in Maine. Of that percentage, about 74% live between two and three hours away. Visitors traveling from Portland Jetport have a 4:24 drive time to the proposed park, while visitors to Acadia National Park have a 2:35 drive time. These results may have implications for whether or not people would take day or overnight trips.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".